Contents

Introduction

The Predictive Ocean Atmosphere Model for Australia (POAMA) is a state-of-the-art seasonal to
inter-annual seasonal forecast system based on a coupled ocean/atmosphere model and
ocean/atmosphere/land observation assimilation systems.

The first version of POAMA (POAMA-1) was developed in a joint project involving the former
Bureau of Meteorology Research Centre (BMRC)
and former CSIRO Division of Marine Research,
with support provided by the Climate Variability in Agriculture Program
(CVAP), a consortium of rural research and development corporations managed by
Land and Water Australia.
The core of the research was carried out by scientists from the Oceanography Group
at BMRC and scientist from the Oceans and Climate Group at CSIRO Marine Research.
This first version went operational in October 2002 and produced routine forecasts of
El Niño conditions.

Since then POAMA continues to be developed. A new version, POAMA-1.5, replaced POAMA-1 as
the Bureau’s operational dynamical seasonal prediction system in September 2007.
POAMA-2 (version P24) replaced POAMA-1.5 in 2011 and was the first operational pseudo
multi-model system. Seasonal forecasts from this system are produced twice monthly.

Operational products consisting of various Sea Surface Temperature indexes for the Pacific
and Indian oceans were made available from POAMA-2 (P24) on the
National Climate Centres web site.
Another set of operational products focussed on the prediction of extreme ocean temperature in the
Great Barrier Reef (for warnings of coral bleaching) are available on the Bureau’s
Oceanographic Services web site.

A new version of POAMA-2, version M24, has been developed as a seamless multi-week to seasonal
forecast system. From 22 May 2013, this version became the new official Bureau seasonal
forecast model. The Burea’s
monthly seasonal climate outlook is based on forecasts from this new system. In addition
to the official Bureau products a suite of new seamless experimental products are available
on the POAMA research web site on a trial basis.

POAMA continues to be developed by scientists from the Centre for Australian Climate and
Weather Research (CAWCR). New versions of the POAMA
model are now based on the new national modelling system
(ACCESS), which is used for all time scales
from weather forecasting to climate change projections.

The new POAMA-2(M24) Seamless Multiweek to Seasonal Forecast System

A new version, POAMA-2 (version M24) is now being run by Bureau operations. This systems forms
the basis for the Bureau operational El Nino forecasts and the monthly seasonal climate outlook,
as well as a range of other products. In addition a suite of experimental products from this
version form the basis for the experimental products on this web site.

Real-time forecasts from POAMA-2(M24) are produced every week by running a 33 member ensemble
starting at 00Z each Monday and Thursday. Operational and experimental products utilise
forecasts produce over the prior two weeks to form a large super-ensemble. For example, the
operational seasonal climate outlook at produced from 3 weeks consecutive sets of forecasts,
i.e. an ensemble of 99 members (3 x 33 weekly forecasts).

POAMA-2(M24) has several features that have led to significant improvements in skill on both
multi-week and seasonal time scales. These include:

A new state of the art assimilation system for using ocean observations,

A multi-model approach using three different configurations of the model (the 33-member
ensemble is made up of 11 member ensembles from each model configuration),

A new state of the art ensemble generation method that generates coupled bred vectors
to initialise the forecasts (unique to M24 version),

Some products utilise a lagged ensemble to increase the ensemble size to 165 and provide
more reliability.

The real-time system is supported by a comprehensive set of hind-casts using exactly the same
system as used for real-time forecasts. This hind-cast set is used to calibrate the real-time
forecasts and assess the skill of the forecast system. These consist of a 33-member ensemble
starting on the 1st, 11th and 21st of each month from 1981 to 2011.

Experimental products are now available on the POAMA web site
(http://poama.bom.gov.au). We are now working on
transitioning some of these experimental products to Bureau operations.

Longer term future (POAMA3 and ACCESS)

Like the development of models for weather forecasting, the development of models for
seasonal prediction is a long term activity with the development of sequential versions of
the system. The core development of the main modules of the future versions of POAMA will be carried
out in a project called ACCESS. ACCESS involves POAMA scientists as well as scientists
from weather forecasting, climate change and ocean prediction. ACCESS brings together
the modelling activities of CAWCR into the development of one common earth system model.
POAMA-3 and beyond will be completely based on the ACCESS model. This will involve a
completely new atmospheric model on the atmospheric model developed by the UK Met Office.
The ocean model will still be based on the GFDL MOM models, but will use their latest
version (MOM4). The ACCESS model also includes a much more sophisticated land-surface models
than currently used by POAMA, called CABLE and was developed at CSIRO. The observations
assimilation system and ensemble generation strategy, which are used to initialise the
forecasts will be based on extensions to the current system.

Why Coupled Models ?

The basis for seasonal prediction lies in variability driven by slow-processes in the climate
system, particularly the ocean. Successful seasonal forecasts are often related to a model’s
ability to reproduce and predict the slowly changing ocean state (e.g. associated with ENSO)
and how this interacts with the atmosphere. The use of coupled atmosphere-ocean models for
seasonal prediction is now commonplace in major international operational centres. These
models couple the ocean and atmosphere and can use all the latest observations from ships,
satellites, ground stations etc. to construct a picture of what the ocean, land and atmosphere
look like today. A picture of how the state of the ocean, land and atmosphere is evolving is
then generated using the coupled model. This model uses mathematical equations representing
the laws of physics.

Unlike existing statistical forecasting systems, coupled models are not limited by historical
relationships and can forecast a new set of climatic conditions. For example, because they
simulate the real world they have the potential to predict how the impacts of one
El Niño might be different to those of another.

One of the benefits of coupled models is that many forecasts (an ensemble) can be produced.
If these are all close together then we can have confidence in the forecast. If they all
differ significantly they can tell us that there is considerable uncertainty in the future
and they give us the range of possibilities. Compared to weather forecasting, coupled model
seasonal forecasting is still in its infancy. Still, great potential lies ahead.

By continuing this collaborative work and investing in further improving our system we
will reap the full benefits of coupled models and provide Australia with a seasonals
forecasting capability second to none.

Our partnerships

Development and evaluation of the POAMA system has benefited from major external
partnerships. These partnerships have contributed to both the development of
POAMA/ACCESS and the evaluation of POAMA forecasts for particular applications. Our main
partnerships are summarised below:

Applying POAMA to agriculture in SW Western Australia, including enhancements to POAMA-2,

Understanding skill and predictability on multi-week scales, including the development
of new multi-week products,

Understanding our ability to predict temperature extremes on multi-week time-scales,
including the development of new extreme temperature prototype products,

Understanding the teleconnections of Australian climate and how well they are simulated
and predicted by POAMA,

Evaluating how well POAMA can predict the Australian monsoon, including the development
of prototype products.

Understanding the skill in predicting the Indian Ocean, how much skill is limited by the
initialisation strategy and investigating ways of improving the initialisation (e.g.
through using new observing systems)

The MCV program makes a very significant contribution to the development and evaluation of POAMA.

PCCSAP:
this program supports the development of seasonal climate predictions using POAMA for some
Pacific Island nations. This includes regional forecasts of temperature and rainfall, ocean
surface temperature forecasts for marine applications e.g. coral bleaching and sea level
forecasting.

GBRMPA: this collaboration supports
the development of seasonal forecasts for coral bleaching risk for the Great Barrier Reef.

Tuna: this collaboration supports the
creation of real time seasonal forecast products for the longline tuna fisheries on the
east Australian coast.

Salmon: this project involves the
development of real time POAMA forecast products for the salmon aquaculture industry in Tasmania.

Prawn: this project supports the
development of real time multi-week and seasonal forecast products for the Queensland prawn
industry.

WIRADA:
this initiative supports the evaluation and application of seasonal climate predictions
from POAMA for hydrological predictions throughout Australia.

WAMSI: this initiative supports
research to evaluate prediction and predictability of the large-scale drivers of
variability of the Western Australian marine environment, particularly focusing on the
impact of ENSO on the Leeuwin Current.